Book Image

Mastering MongoDB 7.0 - Fourth Edition

By : Marko Aleksendrić, Arek Borucki, Leandro Domingues, Malak Abu Hammad, Elie Hannouch, Rajesh Nair, Rachelle Palmer
Book Image

Mastering MongoDB 7.0 - Fourth Edition

By: Marko Aleksendrić, Arek Borucki, Leandro Domingues, Malak Abu Hammad, Elie Hannouch, Rajesh Nair, Rachelle Palmer

Overview of this book

Mastering MongoDB 7.0 explores the latest version of MongoDB, an exceptional NoSQL database solution that aligns with the needs of modern web applications. This book starts with an informative overview of MongoDB’s architecture and developer tools, guiding you through the process of connecting to databases seamlessly. This MongoDB book explores advanced queries in detail, including aggregation pipelines and multi-document ACID transactions. It delves into the capabilities of the MongoDB Atlas developer data platform and the latest features, such as Atlas Vector Search, and their role in AI applications, enabling developers to build applications with the scalability and performance that today’s organizations need. It also covers the creation of resilient search functionality using MongoDB Atlas Search. Mastering MongoDB 7.0’s deep coverage of advanced techniques encompasses everything from role-based access control (RBAC) to user management, auditing practices, and encryption across data, network, and storage layers. By the end of this book, you’ll have developed the skills necessary to create efficient, secure, and high-performing applications using MongoDB. You’ll have the confidence to undertake complex queries, integrate robust applications, and ensure data security to overcome modern data challenges.
Table of Contents (20 chapters)
4
Chapter 4: Connecting to MongoDB

Introduction to indexes

An index is a special data structure that enables faster access to data in a collection, much like an old-school paper encyclopedia index. It is an ordered list of references to the actual contents—the documents—which allows MongoDB to query much faster, often by orders of magnitude. Indexes store values of a specific field or a set of fields, ordered by value. As you will see later in The equality, sort, range (ESR) rule section, MongoDB can return sorted results using the ordering of the index itself.

MongoDB indexes use a data structure known as B-tree, a self-balancing tree data structure that maintains sorted data, and allows sequential access, searches, insertions, and deletions in logarithmic time. The index can be thought of as a list of key-value pairs, where each key is a value of index, and the value of the key-value pair is the document itself. Like an index of a book, the keys are stored in order, and associated with one or more...